arXiv subjects

Alexandre B. Nassif

Publications and source records attributed to Alexandre B. Nassif.

2 recordsLinked to original sources

arXiv2021

Generation of In-group Asset Condition Data for Power System Reliability Assessment

In a power system, unlike some critical and standalone assets that are equipped with condition monitoring devices, the conditions of most regular in-group assets are acquired through periodic inspection work. Due to their large quantities, significant amount of manual inspection effort and sometimes data management issues, it is not uncommon to see the asset condition data in a target study area is unavailable or incomplete. Lack of asset condition data undermines the reliability assessment work. To solve this data problem and enhance data availability, this paper explores an unconventional method-generating numerical and non-numerical asset condition data based on condition degradation, condition correlation and categorical distribution models. Empirical knowledge from human experts can also be incorporated in the modeling process. Also, a probabilistic diversification step can be taken to make the generated numerical condition data probabilistic. This method can generate close-to-real asset condition data and has been validated systematically based on two public datasets. An area reliability assessment example based on cables is given to demonstrate the usefulness of this method and its generated data. This method can also be used to conveniently generate hypothetical asset condition data for research purposes.

cs.CE↗

arXiv2020

Combining Modified Weibull Distribution Models for Power System Reliability Forecast

In recent years, under deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. To help achieve this goal, this research proposes a novel statistical approach to forecast power system asset population reliability. It uniquely combines a few modified Weibull distribution models to build a robust joint forecast model. At first, the classic age based Weibull distribution model is reviewed. In comparison, this paper proposes a few modified Weibull distribution models to incorporate special considerations for power system applications. Furthermore, this paper proposes a novel method to effectively measure the forecast accuracy and evaluate different Weibull distribution models. As a result, for a specific asset population, the suitable model(s) can be selected. More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model to forecast future asset reliability. Finally, the proposed methods were applied to a Canadian utility company for the reliability forecast of electromechanical relays and the results are discussed in detail to demonstrate the practicality and usefulness of this research.

cs.CE↗